Predicting flow state in daily work through continuous sensing of motion rhythm
We have constructed a new application of continuous sensing of human physiological data during daily a business setting. By capturing the subtle changes and differences in motion rhythm detected through an accelerator rather than trying to identify the context of human activities, we are envisioning...
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| creator | Ara, K. Sato, N. Tsuji, S. Wakisaka, Y. Ohkubo, N. Horry, Y. Moriwaki, N. Yano, K. Hayakawa, M. |
| description | We have constructed a new application of continuous sensing of human physiological data during daily a business setting. By capturing the subtle changes and differences in motion rhythm detected through an accelerator rather than trying to identify the context of human activities, we are envisioning the prediction of a person's psychological flow state, i.e., the engagement in one's task. A badge-shaped wearable sensor device called ¿Business Microscope¿ was developed and deployed in a real organization, an office supply firm, for one month to study how effectively flow states could be measured during daily work. We found that even though each subject behaved at different motion rhythms when they were in flow, the consistency of motion rhythm around 2 to 3 Hz was correlated with the richness of flow during work (r=0.47, p |
| doi_str_mv | 10.1109/INSS.2009.5409930 |
| format | Conference Proceeding |
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By capturing the subtle changes and differences in motion rhythm detected through an accelerator rather than trying to identify the context of human activities, we are envisioning the prediction of a person's psychological flow state, i.e., the engagement in one's task. A badge-shaped wearable sensor device called ¿Business Microscope¿ was developed and deployed in a real organization, an office supply firm, for one month to study how effectively flow states could be measured during daily work. We found that even though each subject behaved at different motion rhythms when they were in flow, the consistency of motion rhythm around 2 to 3 Hz was correlated with the richness of flow during work (r=0.47, p<0.01).</abstract><pub>IEEE</pub><doi>10.1109/INSS.2009.5409930</doi><tpages>6</tpages></addata></record> |
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| identifier | ISBN: 1424463130 |
| ispartof | 2009 Sixth International Conference on Networked Sensing Systems (INSS), 2009, p.1-6 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Business Microscope experience sampling method (ESM) flow state Fluid flow measurement Humans Laboratories Microscopy Motion detection Psychology Rhythm Sampling methods sensor network Signal generators wearable device Wearable sensors |
| title | Predicting flow state in daily work through continuous sensing of motion rhythm |
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